Posts

2022.06: One paper accepted by Gene

Our paper, The comprehensive and systematic identification of BLCA-specific SF-regulated, survival-related AS events, is accepted by Gene. In this paper, we comprehensively and systematically identified five SFs and 46 AS events.

2020.09: I was awarded as a candidate of Research Talent Hub (ITF-Funded) in HK

I was awarded as a candidate of Research Talent Hub with the funding from Innovation and Technology Commission of HKSAR from September 2020.

2020.07: One paper accepted by CIKM 2020

Our paper, Recursive Balanced k-Subset Sum Partition for Rule-constrained Resource Allocation, is accepted by CIKM 2020. This is an algorithm paper. In this paper, we proposed a new approach to rule-constrained resource allocation by regarding it as a partition problem.

2020.04: One paper published by IEEE Transactions on Big Data

Our paper, IRDA: Incremental Reinforcement Learning for Dynamic Resource Allocation, is accepted by IEEE Transactions on Big Data. This is a journal paper. We mine the task patterns from the large volume of historical allocation data and propose a reinforcement learning model termed IRDA to learn the allocation strategy in an incremental way.

2020.02: One paper accepted by DASFAA 2020

Our paper, A Big-data-driven Airport Resource Management Engine and Application Tools, is accepted by DASFAA 2020. This is a Demo paper. In this paper, we showcase our research in big data analytics for resource management.

2019.06: Ranked top 10 in HK (6.2%) in EY Data Science Competition, "Smart City"

EY NextWave Data Science competition 2019 focuses on how data can help the next smart city thrive, and boost the mobility of the future. In this competition, systematic data mining and processing ideas are used.

2019.02: One paper published by Journal of Zhengzhou University (Natural Science Edition)

Our paper, A Sequential Attention Based Convolutional Neural Network for Anomaly Detection, is accepted by Journal of Zhengzhou University (Natural Science Edition). This paper focuses on appying a sequential attention based CNN in anomaly detection.